{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Copy Task Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from glob import glob\n",
    "import json\n",
    "import os\n",
    "import sys\n",
    "sys.path.append(os.path.abspath(os.getcwd() + \"./../\"))\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load training history\n",
    "\n",
    "To generate the models and training history used in this notebook, run the following commands:\n",
    "\n",
    "```\n",
    "./train.py --seed 1 --task repeat-copy --checkpoint_interval 500\n",
    "./train.py --seed 10 --task repeat-copy --checkpoint_interval 500\n",
    "./train.py --seed 100 --task repeat-copy --checkpoint_interval 500\n",
    "./train.py --seed 1000 --task repeat-copy --checkpoint_interval 500\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./repeat-copy/repeat-copy-task-1-batch-120000.json',\n",
       " './repeat-copy/repeat-copy-task-10-batch-120000.json',\n",
       " './repeat-copy/repeat-copy-task-100-batch-120000.json',\n",
       " './repeat-copy/repeat-copy-task-1000-batch-120000.json']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batch_num = 120000\n",
    "files = glob(\"./repeat-copy/*-{}.json\".format(batch_num))\n",
    "files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training history (seed x metric x sequence) = (4, 3, 120000)\n"
     ]
    }
   ],
   "source": [
    "# Read the metrics from the .json files\n",
    "history = [json.loads(open(fname, \"rt\").read()) for fname in files]\n",
    "training = np.array([(x['cost'], x['loss'], x['seq_lengths']) for x in history])\n",
    "print(\"Training history (seed x metric x sequence) =\", training.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4, 3, 60)\n"
     ]
    }
   ],
   "source": [
    "# Average every dv values across each (seed, metric)\n",
    "dv = 2000\n",
    "training = training.reshape(len(files), 3, -1, dv).mean(axis=3)\n",
    "print(training.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3, 60)\n",
      "(3, 60)\n"
     ]
    }
   ],
   "source": [
    "# Average the seeds\n",
    "training_mean = training.mean(axis=0)\n",
    "training_std = training.std(axis=0)\n",
    "print(training_mean.shape)\n",
    "print(training_std.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lpdV4n6WlpRw6dKjsVVJSwoQJE1iwYAGLFi2ipKSEP/zhD8THx3Peeeexdu1aFi9eTFFR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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50b138eeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14, 5))\n",
    "\n",
    "# X axis is normalized to thousands\n",
    "x = np.arange(dv / 1000, (batch_num / 1000) + (dv / 1000), dv / 1000)\n",
    "\n",
    "# Plot the cost\n",
    "# plt.plot(x, training_mean[0], 'o-', linewidth=2, label='Cost')\n",
    "plt.errorbar(x, training_mean[0], yerr=training_std[0], fmt='o-', elinewidth=2, linewidth=2, label='Cost')\n",
    "plt.grid()\n",
    "plt.yticks(np.arange(0, training_mean[0][0]+10, 10))\n",
    "plt.ylabel('Cost per sequence (bits)')\n",
    "plt.xlabel('Sequence (thousands)')\n",
    "plt.title('Training Convergence', fontsize=16)\n",
    "\n",
    "ax = plt.axes([.57, .55, .25, .25], facecolor=(0.97, 0.97, 0.97))\n",
    "plt.title(\"BCELoss\")\n",
    "plt.plot(x, training_mean[1], 'r-', label='BCE Loss')\n",
    "plt.yticks(np.arange(0, training_mean[1][0]+0.2, 0.2))\n",
    "plt.grid()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4mc7hAZePDqefn4XXHLlcNiq8p8Ppe+zjIOt1KD0FAWE9HY0QQgghLkBSUlJD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Nu+y5EH5hMOBXBVlmIzDGZz8xRGpK8l0zSNA7ZsBjfuxjZoKP66gwjhGkSpGFMwBICiy8PpXIai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j2M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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50af277240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "loss = history[0]['loss']\n",
    "cost = history[0]['cost']\n",
    "seq_lengths = history[0]['seq_lengths']\n",
    "\n",
    "unique_sls = set(seq_lengths)\n",
    "all_metric = list(zip(range(1, batch_num+1), seq_lengths, loss, cost))\n",
    "\n",
    "fig = plt.figure(figsize=(12, 5))\n",
    "plt.ylabel('Cost per sequence (bits)')\n",
    "plt.xlabel('Iteration (thousands)')\n",
    "plt.title('Training Convergence (Per Sequence Length)', fontsize=16)\n",
    "\n",
    "for sl in unique_sls:\n",
    "    sl_metrics = [i for i in all_metric if i[1] == sl]\n",
    "\n",
    "    x = [i[0] for i in sl_metrics]\n",
    "    y = [i[3] for i in sl_metrics]\n",
    "    \n",
    "    num_pts = len(x) // 50\n",
    "    total_pts = num_pts * 50\n",
    "    \n",
    "    x_mean = [i.mean()/1000 for i in np.split(np.array(x)[:total_pts], num_pts)]\n",
    "    y_mean = [i.mean() for i in np.split(np.array(y)[:total_pts], num_pts)]\n",
    "    \n",
    "    plt.plot(x_mean, y_mean, label='Seq-{}'.format(sl))\n",
    "\n",
    "plt.yticks(np.arange(0, 80, 5))\n",
    "plt.legend(loc=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Evaluate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "from IPython.display import Image as IPythonImage\n",
    "from PIL import Image, ImageDraw, ImageFont\n",
    "import io\n",
    "from tasks.repeatcopytask import dataloader\n",
    "from train import evaluate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from tasks.repeatcopytask import RepeatCopyTaskModelTraining\n",
    "model = RepeatCopyTaskModelTraining()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.net.load_state_dict(torch.load(\"./repeat-copy/repeat-copy-task-10-batch-120000.model\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def cmap(value):\n",
    "    pixval = value * 255\n",
    "    low = 64\n",
    "    high = 240\n",
    "    factor = (255 - low - (255-high)) / 255\n",
    "    return int(low + pixval * factor)\n",
    "\n",
    "def draw_sequence(y, u=12):\n",
    "    seq_len = y.size(0)\n",
    "    seq_width = y.size(2)\n",
    "    inset = u // 8\n",
    "    pad = u // 2\n",
    "    width = seq_len * u + 2 * pad\n",
    "    height = seq_width * u + 2 * pad\n",
    "    im = Image.new('L', (width, height))\n",
    "    draw = ImageDraw.ImageDraw(im)\n",
    "    draw.rectangle([0, 0, width, height], fill=250)\n",
    "    for i in range(seq_len):\n",
    "        for j in range(seq_width):\n",
    "            val = 1 - y[i, 0, j].data[0]\n",
    "            draw.rectangle([pad + i*u + inset,\n",
    "                            pad + j*u + inset,\n",
    "                            pad + (i+1)*u - inset,\n",
    "                            pad + (j+1)*u - inset], fill=cmap(val))\n",
    "\n",
    "    return im\n",
    "\n",
    "def im_to_png_bytes(im):\n",
    "    png = io.BytesIO()\n",
    "    im.save(png, 'PNG')\n",
    "    return bytes(png.getbuffer())\n",
    "\n",
    "def im_vconcat(im1, im2, pad=8):\n",
    "    assert im1.size == im2.size\n",
    "    w, h = im1.size\n",
    "\n",
    "    width = w\n",
    "    height = h * 2 + pad\n",
    "\n",
    "    im = Image.new('L', (width, height), color=255)\n",
    "    im.paste(im1, (0, 0))\n",
    "    im.paste(im2, (0, h+pad))\n",
    "    return im"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def make_eval_plot(y, y_out, u=12):\n",
    "    im_y = draw_sequence(y, u)\n",
    "    im_y_out = draw_sequence(y_out, u)\n",
    "    im = im_vconcat(im_y, im_y_out, u//2)\n",
    "    \n",
    "    w, h = im.size\n",
    "    pad_w = u * 7\n",
    "    im2 = Image.new('L', (w+pad_w, h), color=255)\n",
    "    im2.paste(im, (pad_w, 0))\n",
    "    \n",
    "    # Add text\n",
    "    font = ImageFont.truetype(\"./fonts/PT_Sans-Web-Regular.ttf\", 13)\n",
    "    draw = ImageDraw.ImageDraw(im2)\n",
    "    draw.text((u,4*u), \"Targets\", font=font)\n",
    "    draw.text((u,13*u), \"Outputs\", font=font)\n",
    "    \n",
    "    return im2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def visualize(model, seq_len, max_reps):\n",
    "    seq_len = 8\n",
    "    _, x, y = next(iter(dataloader(1, 1, 8, seq_len, seq_len, 1, max_reps)))\n",
    "    result = evaluate(model.net, model.criterion, x, y)\n",
    "    y_out = result['y_out']\n",
    "    cost = result['cost']\n",
    "    \n",
    "    inp_im = draw_sequence(x, u=10)\n",
    "    eval_im = make_eval_plot(y, y_out, u=10)\n",
    "    return inp_im, eval_im, cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost: 0.0\n"
     ]
    }
   ],
   "source": [
    "inp_im, eval_im, cost = visualize(model, 8, 10)\n",
    "print(\"Cost:\", cost)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAG4AAABuCAAAAADjMHknAAAAzUlEQVR4nO3ZQQqDMBSE4VG66iW8\njYf2Nr1EF111ISELQ0hpSMbH78anET5IYHzR5aORxzpUg7sx9zhP73T93FN15CqPlp6r38uVFH0y\n4eA8uWXsC+iSKq0ZUR8lVeDgfLg5qVLqUH7vWuhV4OAcOZ9Uae1BSBU4OG/OcQdErwIHd2dudq9S\nT4vW50gVODgfbnaq9PnCQqrAwflwjjugPv+FpOhrBwfnyfmkyj9VKV+k6GsHB+fJxUiVXG2peknR\n1w4OzpMbnCqxJzM29wWU7G+k0S2e+AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IPythonImage(im_to_png_bytes(inp_im))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAyoAAADNCAAAAAByC9u8AAAGZklEQVR4nO3dX2idBxnH8eekXROT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\nCkSkAhHbeoh4V4GIVCAiFYhIBSL/BUqDIU3iqoqiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IPythonImage(im_to_png_bytes(eval_im))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create an animated GIF\n",
    "\n",
    "Lets see how the prediction looks like in each checkpoint that we saved. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "seq_len = 10\n",
    "_, x, y = next(iter(dataloader(1, 1, 8, seq_len, seq_len, 1, 10)))\n",
    "\n",
    "frames = []\n",
    "font = ImageFont.truetype(\"./fonts/PT_Sans-Web-Regular.ttf\", 13)\n",
    "for batch_num in range(500, 20500, 500):\n",
    "    model = RepeatCopyTaskModelTraining()\n",
    "    model.net.load_state_dict(torch.load(\"./repeat-copy/repeat-copy-task-10-batch-{}.model\".format(batch_num)))\n",
    "    result = evaluate(model.net, model.criterion, x, y)\n",
    "    y_out = result['y_out']\n",
    "    frame = make_eval_plot(y, y_out, u=10)\n",
    "    \n",
    "    w, h = frame.size\n",
    "    frame_seq = Image.new('L', (w, h+40), color=255)\n",
    "    frame_seq.paste(frame, (0, 40))\n",
    "    \n",
    "    draw = ImageDraw.ImageDraw(frame_seq)\n",
    "    draw.text((10, 10), \"Sequence Num: {} (Cost: {})\".format(batch_num, result['cost']), font=font)\n",
    "    \n",
    "    frames += [frame_seq]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "im = frames[0]\n",
    "im.save(\"./repeat-copy-train-10.gif\", save_all=True, append_images=frames[1:], loop=0, duration=750)"
   ]
  }
 ],
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